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Record W7098784819

Ongoing Fusion Research: Progress on Thick-Liquid Protected IFE Power Plant Design

2003· article· en· W7098784819 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationChinaDivision (mathematics)Power (physics)Executive committeeGovernment (linguistics)Fusion power
DOInot available

Abstract

fetched live from OpenAlex

First, I would like to thank Dr. Wayne Meier, the former Fusion Energy Division (FED) Chair and the 2002-2003 officers and members of the Executive Committee for their effort over the past year in helping FED move forward. I would also like to welcome the new officers and members of the Executive Committee, in particular Dr. Jake Blanchard as Vice-Chair and Dr. Jeff Latkowski as Secretary/Treasurer. In my first message as Chair of the Fusion Energy Division of the American Nuclear Society (ANS), I would like to address a number of topics ranging from national and international fusion developments to the latest news on FED, specifically: the ITER status, the Department of Energy (DOE) FY04 Fusion Budget, FESAC, ANS Division Metrics, and other FED news including TOFE. ITER The US is currently in negotiation to rejoin ITER. With the interest expressed by Korea and China to join ITER, there are now seven parties at the negotiation table: Canada, China, the European Union (EU), Japan, Korea, the Russian Federation and the US. The negotiations are being pursued over a series of meetings at three levels: the Senior

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.006
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0100.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.188
GPT teacher head0.347
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

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